Utilizing Agents To Explore Urban Shrinkage

While more people are living in urban areas than ever before, and this is expected to grow in the coming decades, this growth is not equal. Some cities are actually shrinking, such as Detroit in the United States. The causes of urban shrinkage have been the source of much debate but can be broadly attributed to a combination of factors relating to deindustrialization, suburbanization (i.e., urban sprawl), and demographic withdrawal. The result of shrinking cities, especially in and around the traditional downtown core of the city results in many problems, such as population loss, economic depression (due to loss in tax revenue), a growth in vacant properties, and the contraction of the land and housing markets.

To explore this phenomena, at the upcoming 2020 Spring Simulation Conference we have a paper entitled “Utilizing Agents To Explore Urban Shrinkage: A Case Study Of Detroit.” The motivation for this paper is to explore the housing market in a shrinking city from the micro-level, specifically based on individuals trading interactions via an agent-based model stylized on spatially explicit data of Detroit Tri-county area. Our agent-based model demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to alleviate this issue. For readers wishing to know more about this work, below we provide the abstract to the paper, some figures sketching out some of model logic,  a sample of results and a movie of a representative model run. Similar to our other works, we have a more detailed description of the model following the Overview, Design concepts, and Details (ODD) protocol along with the source code and data needed to run the model at: http://bit.ly/UrbanShrinkage. We do this to aid replication and for others to extend if they see fit. As normal, any thoughts or comments are most welcome.

While the world’s total urban population continues to grow, this growth is not equal. Some cities are declining, resulting in urban shrinkage which is now a global phenomenon. Many problems emerge due to urban shrinkage including population loss, economic depression, vacant properties and the contraction of housing markets. To explore this issue, this paper presents an agent-based model stylized on spatially explicit data of Detroit Tri-county area, an area witnessing urban shrinkage. Specifically, the model examines how micro-level housing trades impact urban shrinkage by capturing interactions between sellers and buyers within different sub-housing markets. The stylized model results highlight not only how we can simulate housing transactions but the aggregate market conditions relating to urban shrinkage (i.e., the contraction of housing markets). To this end, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to alleviate this issue.

Keywords: Urban Shrinkage, Housing Markets, Detroit, Agent-based Modeling, GIS